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DOE OSTI2024

The Interaction Between Climate Forcing and Feedbacks

A Perturbed Parameter Ensemble (PPE) with the Community Atmosphere Model version 6 (CAM6) is used to better understand the sensitivity of aerosol forcing and cloud feedbacks to changes in model processes. Aerosol forcing through aerosol-cloud interactions is mostly negative (a cooling) due to shortwave radiation, while feedbacks are positive or negative in different regions due to contrasting longwave and shortwave effects. Both forcing and feedbacks are related to the mean climate state. Higher magnitude cloud radiative effects generally mean larger magnitude net negative forcing and larger magnitude net positive feedback. Aerosol forcing is broadly related to the susceptibility of clouds to drop number. Feedbacks also related to susceptibility, but to a lesser extent and in different regions to aerosol forcing. Aerosol forcing and cloud feedbacks are anti-correlated in the CAM6 PPE such that stronger negative forcing is associated with stronger positive feedbacks. Even the processes governing forcing and feedback sensitivity in the PPE are similar. These include the warm rain formation process, ice loss processes and deep convective intensity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

On the calculation of internal forces in mechanically stressed polyatomic molecules

We discuss how to define and to compute internal forces in a molecule subjected to mechanical stress. Because of the inherently many-body character of intramolecular interactions, internal forces cannot be uniquely defined without specifying a set of internal coordinates used to describe the molecular structure. When such a set is comprised of 3N − 6 interactomic distances (N being the number of atoms) and includes the bond lengths of interest, we show that the associated forces, while satisfying the equation F = ∂V/∂R (where R is the bond length, F is the internal force in this bond, and V is the potential energy of the molecule), can be determined from the molecular geometry alone. We illustrate these ideas using several toy models ranging from small molecules to a graphene sheet and show that the magnitude of the internal force in a bond is not necessarily a good predictor of its strength in response to mechanical loading. At the same time, analysis of internal forces reveals interesting phenomena such as the force multiplication effect, where weak external forces may, e.g., be used to break strong bonds, and offers insight into the catch-bond phenomenon where chemical reactivity is suppressed through application of a force.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Configurational forces in electronic structure calculations using Kohn-Sham density functional theory

Here we derive the expressions for configurational forces in Kohn-Sham density functional theory, which correspond to the generalized variational force computed as the derivative of the Kohn-Sham energy functional with respect to the position of a material point x. These configurational forces that result from the inner variations of the Kohn-Sham energy functional provide a unified framework to compute atomic forces as well as stress tensor for geometry optimization. Importantly, owing to the variational nature of the formulation, these configurational forces inherently account for the Pulay corrections. The formulation presented in this work treats both pseudopotential and all-electron calculations in a single framework, and employs a local variational real-space formulation of Kohn-Sham density functional theory (DFT) expressed in terms of the nonorthogonal wave functions that is amenable to reduced-order scaling techniques. We demonstrate the accuracy and performance of the proposed configurational force approach on benchmark all-electron and pseudopotential calculations conducted using higher-order finite-element discretization. To this end, we examine the rates of convergence of the finite-element discretization in the computed forces and stresses for various materials systems, and, further, verify the accuracy from finite differencing the energy. Wherever applicable, we also compare the forces and stresses with those obtained from Kohn-Sham DFT calculations employing plane-wave basis (pseudopotential calculations) and Gaussian basis (all-electron calculations). Finally, we verify the accuracy of the forces on large materials systems involving a metallic aluminum nanocluster containing 666 atoms and an alkane chain containing 902 atoms, where the Kohn-Sham electronic ground state is computed using a reduced-order scaling subspace projection technique

36 MATERIALS SCIENCE↗

DOE OSTI2024

Neural Networks to Find the Optimal Forcing for Offsetting the Anthropogenic Climate Change Effects

Abstract Of great relevance to climate engineering is the systematic relationship between the radiative forcing to the climate system and the response of the system, a relationship often represented by the linear response function (LRF) of the system. However, estimating the LRF often becomes an ill-posed inverse problem due to high-dimensionality and nonunique relationships between the forcing and response. Recent advances in machine learning make it possible to address the ill-posed inverse problem through regularization and sparse system fitting. Here, we develop a convolutional neural network (CNN) for regularized inversion. The CNN is trained using the surface temperature responses from a set of Green’s function perturbation experiments as imagery input data together with data sample densification. The resulting CNN model can infer the forcing pattern responsible for the temperature response from out-of-sample forcing scenarios. This promising proof of concept suggests a possible strategy for estimating the optimal forcing to negate certain undesirable effects of climate change. The limited success of this effort underscores the challenges of solving an inverse problem for a climate system with inherent nonlinearity. Significance Statement Predicting the climate response for a given climate forcing is a direct problem, while inferring the forcing for a given desired climate response is often an inverse, ill-posed, problem, posing a new challenge to the climate community. This study makes the first attempt to infer the radiative forcing for a given target pattern of global surface temperature response using a deep learning approach. The resulting deeply trained convolutional neural network inversion model shows promise in capturing the forcing pattern corresponding to a given surface temperature response, with a significant implication on the design of an optimal solar radiation management strategy for curbing global warming. This study also highlights the technical challenges that future research should prioritize in seeking feasible solutions to the inverse climate problem.

Ren, Huiying↗

DOE OSTI2025

The Relative Importance of Forced and Unforced Temperature Patterns in Driving the Time Variation of Low-Cloud Feedback

Abstract Atmospheric models forced with observed sea surface temperatures (SSTs) suggest a trend toward a more-stabilizing cloud feedback in recent decades, partly due to the surface cooling trend in the eastern Pacific (EP) and the warming trend in the western Pacific (WP). Here, we show model evidence that the low-cloud feedback has contributions from both forced and unforced feedback components and that its time variation arises in large part through changes in the relative importance of the two over time, rather than through variations in forced or unforced feedbacks themselves. Initial-condition large ensembles (LEs) suggest that the SST patterns are dominated by unforced variations for 30-yr windows ending prior to the 1980s. In general, unforced SSTs are representative of an ENSO-like pattern, which corresponds to weak low-level stability in the tropics and less-stabilizing low-cloud feedback. Since the 1980s, the forced signals have become stronger, outweighing the unforced signals for the 30-yr windows ending after the 2010s. Forced SSTs are characterized by relatively uniform warming with an enhancement in the WP, corresponding to a more-stabilizing low-cloud feedback in most cases. The time-evolving SST pattern due to this increasing importance of forced signals is the dominant contributor to the recent stabilizing shift of low-cloud feedback in the LEs. Using single-forcing LEs, we further find that if only greenhouse gases evolve with time, the transition to the domination of forced signals occurs 10–20 years earlier compared to the LEs with full forcings, which can be understood through the compensating effect between aerosols and greenhouse gases.

58 GEOSCIENCES↗

DOE OSTI2017

Status Report on Activities of the Systems Assessment Task Force, OECD-NEA Expert Group on Accident Tolerant Fuels for LWRs

The Organization for Economic Cooperation and Development /Nuclear Energy Agency (OECD/NEA) Nuclear Science Committee approved the formation of an Expert Group on Accident Tolerant Fuel (ATF) for LWRs (EGATFL) in 2014. Chaired by Kemal Pasamehmetoglu, INL Associate Laboratory Director for Nuclear Science and Technology, the mandate for the EGATFL defines work under three task forces: (1) Systems Assessment, (2) Cladding and Core Materials, and (3) Fuel Concepts. Scope for the Systems Assessment task force (TF1) includes definition of evaluation metrics for ATF, technology readiness level definition, definition of illustrative scenarios for ATF evaluation, and identification of fuel performance and system codes applicable to ATF evaluation. The identification of irradiation facilities around the world that are being used, or are planned to be used, for the irradiation testing of ATF cladding and fuel materials was later added to the TF1 scope (April 2017). The Cladding and Core Materials (TF2) and Fuel Concepts (TF3) task forces have worked to identify gaps and needs for modeling and experimental demonstration; define key properties of interest; identify the data necessary to perform concept evaluation under normal conditions and illustrative scenarios; identify available infrastructure (internationally) to support experimental needs; and make recommendations on priorities. Where possible, considering proprietary and other export restrictions (e.g., International Traffic in Arms Regulations), the Expert Group has facilitated the sharing of data and lessons learned across the international group membership. The Systems Assessment task force is chaired by Shannon Bragg-Sitton (Idaho National Laboratory [INL], U.S.), the Cladding Task Force is chaired by Marie Moatti (Electricite de France [EdF], France), and the Fuels Task Force is chaired by a Masaki Kurata (Japan Atomic Energy Agency [JAEA], Japan). The original Expert Group mandate was established for June 2014 to June 2016. In April 2016 the Expert Group voted to extend the mandate one additional year to June 2017 in order to complete the task force deliverables; this request was subsequently approved by the Nuclear Science Committee. All reports are currently in final draft and will be submitted to NEA for final formatting/editing in October 2017. A final EGATFL meeting will be held at NEA Headquarters in Paris, France on November 2-3, 2017 to resolve any final comments on the task force reports. This report provides brief summary of the Systems Assessment Task Force deliverable report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change

Detection and attribution (D&A) of forced precipitation change are challenging due to internal variability, limited spatial, and temporal coverage of observational records and model uncertainty. These factors result in a low signal-to-noise ratio of potential regional and even global trends. Here, we use a statistical method – ridge regression – to create physically interpretable fingerprints for the detection of forced changes in mean and extreme precipitation with a high signal-to-noise ratio. The fingerprints are constructed using Coupled Model Intercomparison Project phase 6 (CMIP6) multi-model output masked to match coverage of three gridded precipitation observational datasets – GHCNDEX, HadEX3, and GPCC – and are then applied to these observational datasets to assess the degree of forced change detectable in the real-world climate in the period 1951–2020. We show that the signature of forced change is detected in all three observational datasets for global metrics of mean and extreme precipitation. Forced changes are still detectable from changes in the spatial patterns of precipitation even if the global mean trend is removed from the data. This shows the detection of forced change in mean and extreme precipitation beyond a global mean trend is robust and increases confidence in the detection method's power as well as in climate models' ability to capture the relevant processes that contribute to large-scale patterns of change. We also find, however, that detectability depends on the observational dataset used. Not only coverage differences but also observational uncertainty contribute to dataset disagreement, exemplified by the times of emergence of forced change from internal variability ranging from 1998 to 2004 among datasets. Furthermore, different choices for the period over which the forced trend is computed result in different levels of agreement between observations and model projections. These sensitivities may explain apparent contradictions in recent studies on whether models under- or overestimate the observed forced increase in mean and extreme precipitation. Lastly, the detection fingerprints are found to rely primarily on the signal in the extratropical Northern Hemisphere, which is at least partly due to observational coverage but potentially also due to the presence of a more robust signal in the Northern Hemisphere in general.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

The Radiative Forcing Model Intercomparison Project (RFMIP): Experimental protocol for CMIP6

The phrasing of the first of three questions motivating CMIP6 – “How does the Earth system respond to forcing?” – suggests that forcing is always well-known, yet the radiative forcing to which this question refers has historically been uncertain in coordinated experiments even as understanding of how best to infer radiative forcing has evolved. The Radiative Forcing Model Intercomparison Project (RFMIP) endorsed by CMIP6 seeks to provide a foundation for answering the question through three related activities: (i) accurate characterization of the effective radiative forcing relative to a near-preindustrial baseline and careful diagnosis of the components of this forcing; (ii) assessment of the absolute accuracy of clear-sky radiative transfer parameterizations against reference models on the global scales relevant for climate modeling; and (iii) identification of robust model responses to tightly specified aerosol radiative forcing from 1850 to present. Complete characterization of effective radiative forcing can be accomplished with 180 years (Tier 1) of atmosphere-only simulation using a sea-surface temperature and sea ice concentration climatology derived from the host model's preindustrial control simulation. Assessment of parameterization error requires trivial amounts of computation but the development of small amounts of infrastructure: new, spectrally detailed diagnostic output requested as two snapshots at present-day and preindustrial conditions, and results from the model's radiation code applied to specified atmospheric conditions. In conclusion, the search for robust responses to aerosol changes relies on the CMIP6 specification of anthropogenic aerosol properties; models using this specification can contribute to RFMIP with no additional simulation, while those using a full aerosol model are requested to perform at least one and up to four 165-year coupled ocean–atmosphere simulations at Tier 1.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Interaction force measurement between E. coli cells and nanoparticles immobilized surfaces by using AFM

To better understand environmental behaviors of nanoparticles (NPs), we used the atomic force microscopy (AFM) to measure interaction forces between E. coli cells and NPs immobilized on surfaces in an aqueous environment. The results showed that adhesion force strength was significantly influenced by particle size for both hematite ( -Fe2 O3 ) and corundum ( -Al2 O3 ) NPs whereas the effect on the repulsive force was not observed. The adhesion force decreased from 6.3 0.7 nN to 0.8 0.4 nN as hematite NPs increased from 26 nm to 98 nm in diameter. Corundum NPs exhibited a similar dependence of adhesion force on particle size. The Johnson Kendall Roberts (JKR) model was employed to estimate the contact area between E. coli cells and NPs, and based on the JKR model a new model that considers local effective contact area was developed. The prediction of the new model matched the size dependence of adhesion force in experimental results. Size effects on adhesion forces may originate from the difference in local effective contact areas as supported by our model. These findings provide fundamental information for interpreting the environmental behaviors and biological interactions of NPs, which barely have been addressed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Surface forces: Surface roughness in theory and experiment

A method of incorporating surface roughness into theoretical calculations of surface forces is presented. The model contains two chief elements. First, surface roughness is represented as a probability distribution of surface heights around an average surface height. A roughness-averaged force is determined by taking an average of the classic flat-surface force, weighing all possible separation distances against the probability distributions of surface heights. Second the model adds a repulsive contact force due to the elastic contact of asperities. We derive a simple analytic expression for the contact force. The general impact of roughness is to amplify the long range behaviour of noncontact (DLVO) forces. The impact of the elastic contact force is to provide a repulsive wall which is felt at a separation between surfaces that scales with the root-mean-square (RMS) roughness of the surfaces. The model therefore provides a means of distinguishing between “true zero,” where the separation between the average centres of each surface is zero, and “apparent zero,” defined by the onset of the repulsive contact wall. A normal distribution may be assumed for the surface probability distribution, characterised by the RMS roughness measured by atomic force microscopy (AFM). Alternatively the probability distribution may be defined by the histogram of heights measured by AFM. Both methods of treating surface roughness are compared against the classic smooth surface calculation and experimental AFM measurement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Strong Attraction and Adhesion Forces of Dust Particles by System Voltages of Photovoltaic Modules

We report for the first time on direct measurements using atomic force microscopy (AFM) of electric field induced attraction and adhesion forces associated with soiling on photovoltaic (PV) modules. Real dust particles and silica spheres as surrogate to simulating dust particles were glued to AFM probe cantilevers. The electric field induced force (Fes) was measured via AFM force-distance (f-z) curves, where the electric field was generated by applying a voltage (Vs) to a simulated PV module. Fes and van der Waals (Fvw) force contributions could be separated with the f-z curves. The results show that Fes ~2.5 u N on dust particles is ~5 times larger than Fvw ~0.5 u N at even Vs = -100 V (i.e., similar to large-module operating voltages). Fes increases by an order of magnitude as the applied potential increases from Vs = -100 V to Vs = -500 V. These adhesion forces are by far the strongest that we have measured using the AFM technique for 'initial' contact of particles. Furthermore, unlike the more typical short-range forces of Fvw and liquid bridge, Fes extends sub-millimeters to a millimeter beyond the PV module surface, creating large attraction forces to even uncharged dust particles (i.e., via induced dipoles) in the air. These results indicate that the high voltages typically used with PV arrays today will attract more dust particles from the air, hold the dust particles to the surface very strongly, and potentially induce other PV module surface effects, all of which could increase the power production losses because of soiling.

14 SOLAR ENERGY↗

DOE OSTI2018

Investigating the Linear Dependence of Direct and Indirect Radiative Forcing on Emission of Carbonaceous Aerosols in a Global Climate Model

Herein, the relationship between forcing and emission is investigated for black carbon (BC) and primary organic carbon (OC) emitted from North America and Asia. Direct and indirect radiative forcing (DRF and IRF) of BC and OC are simulated with CAM5.1. Two diagnostics are introduced to aid policy-relevant discussions: linearity and emission-normalized forcing. DRF is linearly related to emission for both BC and OC from two regions, and the linear relationship is similar, within 15%. IRF is linear in emissions when emissions are lower and regions are far from sources (North American BC and OC). Indirect radiative forcing is sublinear for strong sources and near-source regions (Asian OC). Emission-normalized IRF in North America is two to four times higher than that in Asia. The difference among regions and species is primarily caused by particle density as high density of BC results in fewer emitted particles and by the processes for accumulation mode particles to become cloud condensation nuclei and then to activate into cloud droplet. Lower emission-normalized IRF in more polluted regions means that reductions of OC in these regions would be relatively climate-neutral rather than causing significant warming via IRF reduction. An optimal aggregation area (30° × 30°) is identified for analysis of the forcing-to-emission relationship. For IRF, only 15–40% of the Earth’s surface is significantly affected by an emission region, but forcing in these regions comprises most of the global impact. Emission-normalized forcing can be used to estimate forcing changes due to emission reductions, as long as causes of nonlinearity are identified and considered.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

An improved proximity force approximation for electrostatics

A quite straightforward approximation for the electrostatic interaction between two perfectly conducting surfaces suggests itself when the distance between them is much smaller than the characteristic lengths associated with their shapes. Indeed, in the so called 'proximity force approximation' the electrostatic force is evaluated by first dividing each surface into a set of small flat patches, and then adding up the forces due two opposite pairs, the contributions of which are approximated as due to pairs of parallel planes. This approximation has been widely and successfully applied in different contexts, ranging from nuclear physics to Casimir effect calculations. We present here an improvement on this approximation, based on a derivative expansion for the electrostatic energy contained between the surfaces. The results obtained could be useful for discussing the geometric dependence of the electrostatic force, and also as a convenient benchmark for numerical analyses of the tip-sample electrostatic interaction in atomic force microscopes. - Highlights: Black-Right-Pointing-Pointer The proximity force approximation (PFA) has been widely used in different areas. Black-Right-Pointing-Pointer The PFA can be improved using a derivative expansion in the shape of the surfaces. Black-Right-Pointing-Pointer We use the improved PFA to compute electrostatic forces between conductors. Black-Right-Pointing-Pointer The results can be used as an analytic benchmark for numerical calculations in AFM. Black-Right-Pointing-Pointer Insight is provided for people who use the PFA to compute nuclear and Casimir forces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

AFM force measurements of the gp120-sCD4 and gp120 or CD4 antigen-antibody interactions

Highlights: {yields} The unbinding force of sCD4-gp120 interaction was 25.45 {+-} 20.46 pN. {yields} The unbinding force of CD4 antigen-antibody interaction was 51.22 {+-} 34.64 pN. {yields} The unbinding force of gp120 antigen-antibody interaction was 89.87 {+-} 44.63 pN. {yields} The interaction forces between various HIV inhibitors and the target molecules are significantly different. {yields} Functionalizing on AFM tip or substrate of an interaction pair caused different results. -- Abstract: Soluble CD4 (sCD4), anti-CD4 antibody, and anti-gp120 antibody have long been regarded as entry inhibitors in human immunodeficiency virus (HIV) therapy. However, the interactions between these HIV entry inhibitors and corresponding target molecules are still poorly understood. In this study, atomic force microscopy (AFM) was utilized to investigate the interaction forces among them. We found that the unbinding forces of sCD4-gp120 interaction, CD4 antigen-antibody interaction, and gp120 antigen-antibody interaction were 25.45 {+-} 20.46, 51.22 {+-} 34.64, and 89.87 {+-} 44.63 pN, respectively, which may provide important mechanical information for understanding the effects of viral entry inhibitors on HIV infection. Moreover, we found that the functionalization of an interaction pair on AFM tip or substrate significantly influenced the results, implying that we must perform AFM force measurement and analyze the data with more caution.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

An adaptive model-free robotic force control strategy for hydrodynamic real-time hybrid simulation of floating offshore wind turbines

Real-time hybrid simulation (RTHS) - a cyber-physical testing approach - promises to enhance the simulation fidelity of the model-scale experiments used to prototype floating offshore wind turbines (FOWTs). In hydrodynamic RTHS (hydro-RTHS), actuators emulate aerodynamic forces on model-scale FOWT specimens subjected to physical waves in a hydrodynamic laboratory. Robotic arms are promising candidates for actuation in hydro-RTHS due to their compact multi-degree-of-freedom (DOF) capabilities. Unlike classical RTHS for seismic applications, which typically relies on displacement control, hydro-RTHS requires 6-DOF force control on newly designed floating prototypes in a model-scale setting, which presents significant challenges, including modeling uncertainties, directional asymmetry, configuration drift, bandwidth limitations, and time-varying delays. To mitigate these constraints without extensive pre-test calibration, this study proposes an adaptive model-free robotic force control strategy that combines task-space explicit force control with a secondary joint-space pose-keeping task. The Adaptive Feedforward Compensator (AFC) is integrated into the force control loop to compensate for time-varying delay. Experimental testing was conducted using a Franka Emika Panda robotic arm with a 1:50 scale FOWT specimen under operational wind and wave conditions. Results demonstrate stable and consistent 6-DOF force tracking. Effective delay compensation was observed, with low-frequency delay reductions ranging from 71.4% to 91.8% and improvements in low-frequency surge force tracking of 25.0% to 52.1%. This study enhances robotic actuation performance in hydro-RTHS and introduces a force control strategy that supports reliable robotic operation in uncertain floating environments. Future work will explore disturbance-observer mechanisms to further enhance wave rejection capabilities under extreme wind and wave conditions.

17 WIND ENERGY↗

DOE OSTI2014

Multi-dimensional modelling of electrostatic force distance curve over dielectric surface: Influence of tip geometry and correlation with experiment

Electric Force-Distance Curves (EFDC) is one of the ways whereby electrical charges trapped at the surface of dielectric materials can be probed. To reach a quantitative analysis of stored charge quantities, measurements using an Atomic Force Microscope (AFM) must go with an appropriate simulation of electrostatic forces at play in the method. This is the objective of this work, where simulation results for the electrostatic force between an AFM sensor and the dielectric surface are presented for different bias voltages on the tip. The aim is to analyse force-distance curves modification induced by electrostatic charges. The sensor is composed by a cantilever supporting a pyramidal tip terminated by a spherical apex. The contribution to force from cantilever is neglected here. A model of force curve has been developed using the Finite Volume Method. The scheme is based on the Polynomial Reconstruction Operator—PRO-scheme. First results of the computation of electrostatic force for different tip–sample distances (from 0 to 600 nm) and for different DC voltages applied to the tip (6 to 20 V) are shown and compared with experimental data in order to validate our approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Significant impact of forcing uncertainty in a large ensemble of climate model simulations

Forcing due to solar and volcanic variability, on the natural side, and greenhouse gas and aerosol emissions, on the anthropogenic side, are the main inputs to climate models. Reliable climate model simulations of past and future climate change depend crucially upon them. Here we analyze large ensembles of simulations using a comprehensive Earth System Model to quantify uncertainties in global climate change attributable to differences in prescribed forcings. The different forcings considered here are those used in the two most recent phases of the Coupled Model Intercomparison Project (CMIP), namely CMIP5 and CMIP6. We show significant differences in simulated global surface air temperature due to volcanic aerosol forcing in the second half of the 19th century and in the early 21st century. The latter arise from small-to-moderate eruptions incorporated in CMIP6 simulations but not in CMIP5 simulations. We also find significant differences in global surface air temperature and Arctic sea ice area due to anthropogenic aerosol forcing in the second half of the 20th century and early 21st century. These differences are as large as those obtained in different versions of an Earth System Model employing identical forcings. In simulations from 2015 to 2100, we find significant differences in the rates of projected global warming arising from CMIP5 and CMIP6 concentration pathways that differ slightly but are equivalent in terms of their nominal radiative forcing levels in 2100. Our results highlight the influence of assumptions about natural and anthropogenic aerosol loadings on carbon budgets, the likelihood of meeting Paris targets, and the equivalence of future forcing scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Active liquid crystals powered by force-sensing DNA-motor clusters

Significance Single-molecule techniques have elucidated how isolated molecular motors generate piconewton forces with unprecedented detail. However, in diverse biological and synthetic settings, force-generating proteins collectively power nonequilibrium dynamics, including continuous large-scale rearrangements and persistent fluid flows. Characterizing motor-generated forces in these dense and dynamical environments remains a challenge. We assembled a reversible DNA-based force-sensing probe that, by an optical readout, reveals the molecular arrangements and the force loads experienced by kinesin motors. These probes provide insight into motor-generated forces that collectively power the unique dynamics of microtubule-based active nematics, a noteworthy example of an internally driven active matter system. DNA-based force probes can be extended to study forces and stresses in various synthetic systems as well as diverse cellular environments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗